Currently, there are many hundreds of thousands of calls a day between prison inmates—who are incarcerated in federal, state, and local correctional facilities—and friends, acquaintances, or family members. State Department of Corrections (“DOC”) or Federal Bureau of Prisons (“BOP”) personnel attempt to listen to call conversations for incidents or indications of threats, conspiracies, illegal drug trafficking, and/or the like. There are, however, many hundreds of conversations and a shortage of DOC or BOP personnel, thus making monitoring of calls difficult. Like highway patrol officers attempting to slow traffic by randomly choosing a road on which to catch speeders, random call monitoring of prison inmates may represent a waste of time and resources.
Hence, there is a need for more robust and scalable solutions for implementing call monitoring, and, in particular embodiments, to methods, systems, apparatuses, and computer software for implementing self learning call monitoring in the corrections facility context.